Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 901

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

A new Voronoi-based surface reconstruction algorithm

Open access
Amenta, Nina, Bern, Marshall, Kamvysselis, Manolis·1998·Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98

Abstract

We describe our experience with a new algorithm for the reconstruction of surfaces from unorganized sample points in IR 3 .The al- gorithm is the first for this problem with provable guarantees.Given a "good sample" from a smooth surface, the output is guaranteed to be topologically correct and convergent to the original surface as the sampling density increases.The definition of a good sample is itself interesting: the required sampling density varies locally, rigorously capturing the intuitive notion that featureless areas can be reconstructed from fewer samples.The output mesh interpolates, rather than approximates, the input points.Our algorithm is based on the three-dimensional Voronoi diagram.Given a good program for this fundamental subroutine, the algorithm is quite easy to implement.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/280814.280947

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 6 references

Cited by

See all 901

Metadata

Authors
Amenta, N., Bern, M., & Kamvysselis, M.
Venue
Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98
Publisher
ACM Press
Published
1998
Pages
415-421
OpenAlex
W2158905481
Cited by
901
References
6
FWCI
49.98
Type
conference paper
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A new Voronoi-based surface reconstruction algorithm. https://app.cochat.ai/papers/10.1145/280814.280947
The paper
Amenta, N., Bern, M., & Kamvysselis, M. (1998). A new Voronoi-based surface reconstruction algorithm. Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98. https://doi.org/10.1145/280814.280947

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.